If you want to implement a robust data integration process like ETL, your business will need tools for data transformation. These data transformation tools enable businesses to consolidate raw data from multiple data sources and add critical information to it before analysis. Modern mobile apps and web solutions rely on data, and if your organization doesn’t have strong data transformation tools, its software might suffer.
This post will explore some of the top data transformation tools available to businesses. Of course, we can’t cover every available data transformation tool. Still, we will look at some of the industry’s leading options and do a brief rundown of what they offer so your business can make an informed decision.
Top Data Transformation Tools
When choosing data transformation tools for your business, it is important to consider your needs. For example, do you want HiTech integrations and additional Machine Learning features? Is data security your organization’s top priority? Before reviewing different data transformation tools, take the time to consider your data management needs.
Once you and your data engineers have established your data priorities, you can choose the best data transformation tool for your business. Here are some of the top data transformation tools your organization should take the time to consider:
- AWS Glue
For data engineers with experience with SQL, dbt might be the best data transformation tool. With dbt, data engineers can manage entire data pipelines and write custom code to quickly enable data transformation. Using dbt, data engineers can easily turn SQL queries into views and tables in most major data warehouses, including BigQuery, Snowflake, and Redshift.
In addition, dbt natively supports Git integrations, modularity, logging, and version control. Plus, dbt has a “ref function” feature that allows data engineers to reference one data model within another. This feature is helpful for generating dependency graphs and updating them as changes are made.
This data transformation tool is great for experienced data engineers. However, for less technically experienced team members, dbt might be too difficult to use effectively. Another great thing about dbt Core is that it is open-source and free to use. However, if you have a larger team and want access for multiple data engineers, dbt Cloud is priced at $50 per month per user.
EasyMorph is a great data transformation tool for less technically advanced users. EasyMorph enables businesses to automate complex data transformations and other repetitive tasks without requiring them to write a single line of code. In addition, EasyMorph comes with over 200 actions and functions right out of the box.
You don’t need a team of data engineers to get value out of EasyMorph. Anyone in your business can use this Windows-based data transformation tool to create advanced workflows with conditional branching, parameters, and loops because EasyMorph is a visual tool. The one downside to EasyMorph is that there is not as much support for data output as there is for data input.
EasyMorph offers a free version for organizations to try. Pricing for this tool ranges from $250 for three months or $750 for a full year.
AWS Glue is an AWS service that enables businesses to find, process, and merge data for further analysis. Businesses that use other AWS services will enjoy AWS Glue because it integrates seamlessly with everything AWS offers. In addition, AWS Glue is serverless, so your organization’s data engineers won’t have to worry about managing infrastructure, and your business will only pay for the resources it uses.
AWS Glue enables businesses to set up and manage ETL jobs visually. When AWS Glue transforms data from multiple sources, it automatically identifies the format and suggests the appropriate schema for the data transformation.
As previously mentioned, AWS Glue is a serverless service that charges on a per-use basis, which means AWS Glue is a cost-effective data transformation solution.
Matillion is a great data transformation tool for technical experts and beginners. Skilled data engineers can define data functions in SQL, and beginners can use a simple point-and-click system to transform data. In addition, Matillion integrates seamlessly with popular data warehousing solutions like Azure Synapse, Redshift, Snowflake, and BigQuery to transform large sets of raw data on demand.
Matillion simplifies the ETL data integration process with more than 70 pre-built connectors. Plus, with Matillion, your organization can get expert technical support for its transformation projects at no additional cost. As a result, Matillion is the best data transformation tool for teams with mixed skill sets.
Matillion offers a free-trial version for organizations to try and flexible pricing plans so your business can get the services it needs at a price it can afford.
Dataform is an open-source data transformation tool that enables businesses to manage all of their data processes in cloud data warehouses. It integrates seamlessly with most of the biggest cloud data warehouses, including Redshift, Snowflake, BigQuery, and Panoply. In addition, data engineers well-versed in SQL can use the command line function to build powerful data transformation pipelines using Dataform.
Dataform is similar to dbt in that it includes a “ref function” that enables data engineers to easily create data dependencies between tables and data sources so that they can spend more time analyzing data and less time managing data infrastructure. If you don’t want to spend time coding data transformation rules, Dataform offers a paid version called Dataform Web that comes packaged with a robust IDE.
Dataform is a powerful data transformation tool for data engineers that use SQL. Many argue that Dataform is more user-friendly than dbt, but Dataform is supported by a smaller community of developers and used by fewer companies. Dataform is open-source and free to use, but there is a waitlist to access it. Dataform Web begins at $150 per month for five user accounts.
Apache Airflow is a well-rounded data transformation tool. After configuring your organization’s codebase, your data engineers can perform and manage the entire ETL data integration process using Airflow. Airflow can also be used to organize, schedule, and monitor complicated data flows.
In Airflow, data engineers and developers can quickly transform data by writing Python code. This data transformation tool is powerful but best suited for organizations that use Python ETL tools. In addition, Airflow is open-source and free for organizations to use.
If your business is looking for good data transformation tools, there are plenty of great options listed in this post. However, we haven’t been able to fully list all available options, so you should still do your due diligence and explore all available options. If you need help determining which tools for data transformation are best suited for your data needs, reach out to an experienced app development partner.